Leland Stanford Junior University

Guangdong Oppo Mobile Telecommunications Corp., Ltd.

Forty Seven, Inc.

Medarex Inc.

E. R. Squibb Sons, Inc.

Jie Liu

Irving L Weissman

Ravindra Majeti

Jens-Peter Volkmer

Yang Zhou

Stephen Willingham

Susan Sweeney Prohaska

Anne Kathrin Volkmer

Maureen C Howard

Mark P Chao

Kavitha Sompalli

David J King

Aaron Michael Ring

Ronald Levy

Maureen Howard

Haichun Huang

Josephine M Cardarelli

David B Passmore

Crystal L Mackall

Chin Pan

Chetana Rao-Naik

Dawn M Tanamachi

Robbie Majzner

Wan-Jen Hong

Alasdair Fraser Bell

Shoshana Levy

Aurelien Marabelle

Ranjani Rajapaksa

Felipe Vences-Catalan

Chiung-Chi Kuo

Rebecca Richards

To Uyen Thi Do

Sharline Chen

David John King

Anne K Volkmer

David King

A face detection device based on a convolutional neural network is provided. The device includes a feature extractor assembly and a detector assembly. The feature extractor assembly includes a first feature extractor, a second feature extractor and a third feature extractor. The first feature extractor is used to apply a first set of convolution kernels on an input grayscale image thereby generate a set of basic feature maps. The second feature extractor is used to apply a second set of convolution kernels on the set of basic feature maps and thereby generate more than one set of intermediate feature maps, which are concatenated. The third feature extractor is used to perform at least one convolution operation on a concatenated layer. The detector assembly includes at least one detector whose input is derived from one of the second feature extractor and the third feature extractor.

Face detection device, method and face unlock system

Antigen binding domain polypeptides (ABD) specific for human CD93 are provided, which ABD may be formatted as antibodies, as chimeric antigen receptors, and the like. T cells comprising an anti-CD93 CAR are useful in the treatment of cancer, e.g. hematologic malignancies.

Therapeutic antigen binding proteins specific for CD93 and methods of use thereof

An image processing method and device, an equipment, and a computer-readable storage medium are provided. The method includes the following. An image is obtained. Object detection is performed on the image with an object detection network to obtain an object detection result. The object detection network is a network obtained by performing object detection on sample images in a sample image set based on at least one cluster center value with an initial object detection network and training iteratively the initial object detection network based on results of the object detection. The at least one cluster center value is obtained by clustering labeled regions in a labeled region set corresponding to the sample image set based on preset attribute information. The image is processed based on the object detection result.

Image processing method and device, equipment, and computer-readable storage medium

Methods are provided herein for determining and administering optimized dosing of therapeutic anti-D47 agents, in a schedule that provides safe escalation of dose while achieving a therapeutic level in a clinically effective period of time. The methods can comprise the steps of clearance, escalation, and maintenance. In one embodiment the dosing regimen administers an initial (i) sub-therapeutic dose of an anti-CD47 agent or (ii) a cytoreductive therapy to achieve a safe level of circulating tumor cells for subsequent treatment (clearance); escalating the dose of an anti-CD47 agent until a therapeutic dose is reached (escalation); and maintaining the therapeutic dose for a period of time sufficient to reduce tumor cells in the bone marrow of the patient (maintenance). In an alternative dosing regimen, a patient determined to have a safe level of circulating tumor cells at presentation is treated by the steps of escalation and maintenance without initial clearance.

Dosing parameters for CD47 targeting therapies to hematologic malignancies

The embodiments of the present disclosure disclose an object detection method and system, and a non-transitory computer-readable medium. In the object detection method, multiple candidate bounding boxes of an interest object in a current image frame are obtained. Based on a determined bounding box of the interest object in a previous image frame, the multiple candidate bounding boxes are filtered to obtain a determined bounding box of the interest object in the current image frame.

Object detection method and system, and non-transitory computer-readable medium

An evaluating method and a system for face verification, and a computer storage medium. The method comprises: obtaining a querying dataset and a training dataset, wherein the querying dataset comprises querying images, and the training dataset comprises training images; generating verification pairs and an evaluation list respectively according to the querying dataset and the training dataset; wherein the evaluation list comprises the querying images and the training images; determining feature information based on the evaluation list; establishing correspondences between identifiers and features according to first identifiers of the querying images, second identifiers of the training image, and the feature information; and determining evaluation results of the verification pairs according to the correspondences between the identifiers and the features.

Evaluating method and system for face verification, and computer storage medium

Methods are provided for treating a subject with a therapeutic dose of anti-CD47 agent by administering a primer agent prior to administering a therapeutically effective dose of an anti-CD47 agent to the subject.

Methods for achieving therapeutically effective doses of anti-CD47 agents

Methods for treating myeloma by achieving therapeutically effective doses of anti-CD47 antibody

Provided are a hand pose estimation method and apparatus, and a storage medium in embodiments of the present disclosure disclose. The method includes: obtaining a feature map corresponding to a hand depth image; inputting the feature map into an image feature extraction network to obtain an image information set feature map corresponding to the hand depth image; up-sampling the image information set feature map to obtain a target resolution feature map; inputting the target resolution feature map into a predetermined depth classification network to obtain depth maps corresponding to hand key points in the hand depth image, wherein the predetermined depth classification network is configured to distinguish hand key points of different depths; and determining, based on the depth maps, depth values corresponding to the hand key points to perform hand pose estimation.

Method and apparatus for determining a depth value of hand posture that involves acquiring a hand depth image map and image information feature map is up-sampled to obtain resolution feature map, and non transitory computer-readable storage medium

A data cleaning method is provided. The method incudes: acquiring a training face dataset, the training face dataset including a plurality of training images each labeled with a person ID; acquiring a candidate face verification model and training the candidate face verification model by the plurality of training images; acquiring a plurality of feature embeddings from the candidate face verification model after training, and determining a similarity between the average feature embedding of one person ID and each image labeled as the same person ID; extracting at least one training image whose similarity is smaller than a similarity threshold from the plurality of training images; and excluding the at least one extracted training image in response to receiving a confirmation signal.

Data cleaning device, data cleaning method and face verification method

Provided are a hand gesture detection method and device, and a computer storage medium. The method includes: obtaining an initial depth image including a hand to be detected, and performing detection processing on the initial depth image by using a backbone feature extractor and a bounding box detection model to obtain initial bounding boxes and a first feature map corresponding to the hand to be detected; determining one of the initial bounding boxes as a target bounding box; cropping, based on the target bounding box, the first feature map by using RoIAlign feature extractor, to obtain a second feature map corresponding to the hand to be detected; and performing, based on the second feature map, a three-dimensional gesture estimation processing on the hand to be detected by using a gesture estimation model to obtain a gesture detection result of the hand to be detected.

Hand gesture detection method involves acquiring initial depth image using backbone and apparatus, and non-transitory computer-readable storage medium

Methods are provided herein for determining and administering optimized dosing of therapeutic anti-CD47 agents, in a schedule that provides safe escalation of dose while achieving a therapeutic level in a clinically effective period of time. The methods can comprise the steps of clearance, escalation, and maintenance. In one embodiment the dosing regimen administers an initial (i) sub-therapeutic dose of an anti-CD47 agent or (ii) a cytoreductive therapy to achieve a safe level of circulating tumor cells for subsequent treatment (clearance); escalating the dose of an anti-CD47 agent until a therapeutic dose is reached (escalation); and maintaining the therapeutic dose for a period of time sufficient to reduce tumor cells in the bone marrow of the patient (maintenance). In an alternative dosing regimen, a patient determined to have a safe level of circulating tumor cells at presentation is treated by the steps of escalation and maintenance without initial clearance.

Provided are a hand pose estimation method, a device and a computer storage medium. The method may include: determining a classification logic map corresponding to each of a plurality of key-points, the plurality of key-points may represent key nodes of a skeleton of a target hand skeleton, a first key-point may be any one of the plurality of key-points; determining, based on a preset classification map and the classification logic map corresponding to the first key-point, co-ordinate information of the first key-point; and obtaining a pose estimation result of the target hand, in response to determining the co-ordinate information corresponding to each of the plurality of key-points.

Hand pose estimation method, device and storage medium

Provided are a gesture recognition method and apparatus, and a storage medium. The method includes: obtaining a first feature map corresponding to a target region in a depth image, and determining a target key point from the first feature map; establishing a three-dimensional coordinate system in the first feature map by using the target key point, and predicting other three-dimensional coordinates of other key points in the three-dimensional coordinate system, the other key points being key points other than the target key point in the first feature map; and determining, based on the target key point and the other three-dimensional coordinates, a plurality of absolute coordinates of a plurality of key points, to determine a gesture of a target recognition object in the target region based on the plurality of absolute coordinates, the plurality of key points including the target key point and the other key points.

Gesture recognition method and apparatus, and storage medium

The invention provides antibodies specifically binding to c-Kit and methods of using such antibodies in stem cell replacement and treatment of cancer.

Growing community of inventors

Palo Alto, CA, United States of America

Jie Liu